Literature DB >> 21399912

An image processing application for the localization and segmentation of lymphoblast cell using peripheral blood images.

Hayan T Madhloom1, Sameem Abdul Kareem, Hany Ariffin.   

Abstract

An important preliminary step in the diagnosis of leukemia is the visual examination of the patient's peripheral blood smear under the microscope. Morphological changes in the white blood cells can be an indicator of the nature and severity of the disease. Manual techniques are labor intensive, slow, error prone and costly. A computerized system can be used as a supportive tool for the specialist in order to enhance and accelerate the morphological analysis process. This research present a new method that integrates color features with the morphological reconstruction to localize and isolate lymphoblast cells from a microscope image that contains many cells. The localization and segmentation are conducted using a proposed method that consists of an integration of several digital image processing techniques. 180 microscopic blood images were tested, and the proposed framework managed to obtain 100% accuracy for the localization of the lymphoblast cells and separate it from the image scene. The results obtained indicate that the proposed method can be safely used for the purpose of lymphoblast cells localization and segmentation and subsequently, aiding the diagnosis of leukemia.

Entities:  

Mesh:

Year:  2011        PMID: 21399912     DOI: 10.1007/s10916-011-9679-0

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  3 in total

1.  Morphological granulometric features of nucleus in automatic bone marrow white blood cell classification.

Authors:  Nipon Theera-Umpon; Sompong Dhompongsa
Journal:  IEEE Trans Inf Technol Biomed       Date:  2007-05

Review 2.  Leukemia and the disruption of normal hematopoiesis.

Authors:  C L Sawyers; C T Denny; O N Witte
Journal:  Cell       Date:  1991-01-25       Impact factor: 41.582

3.  A framework for white blood cell segmentation in microscopic blood images using digital image processing.

Authors:  Farnoosh Sadeghian; Zainina Seman; Abdul Rahman Ramli; Badrul Hisham Abdul Kahar; M-Iqbal Saripan
Journal:  Biol Proced Online       Date:  2009-06-11       Impact factor: 3.244

  3 in total
  6 in total

1.  Semiautomated Segmentation and Measurement of Cytoplasmic Vacuoles in a Neutrophil With General-Purpose Image Analysis Software.

Authors:  Maki Mizukami; Misaki Yamada; Sayaka Fukui; Nao Fujimoto; Shigeru Yoshida; Sanae Kaga; Keiko Obata; Shigeki Jin; Keiko Miwa; Nobuo Masauzi
Journal:  J Clin Lab Anal       Date:  2016-04-07       Impact factor: 2.352

2.  Detection of acute lymphoblastic leukemia using image segmentation and data mining algorithms.

Authors:  Vasundhara Acharya; Preetham Kumar
Journal:  Med Biol Eng Comput       Date:  2019-06-14       Impact factor: 2.602

3.  Development of a Robust Algorithm for Detection of Nuclei and Classification of White Blood Cells in Peripheral Blood Smear Images.

Authors:  Roopa B Hegde; Keerthana Prasad; Harishchandra Hebbar; Brij Mohan Kumar Singh
Journal:  J Med Syst       Date:  2018-05-02       Impact factor: 4.460

4.  Automatic Identification of Human Erythrocytes in Microscopic Fecal Specimens.

Authors:  Lin Liu; Haoting Lei; Jing Zhang; Yang Yuan; Zhenglong Zhang; Juanxiu Liu; Yu Xie; Guangming Ni; Yong Liu
Journal:  J Med Syst       Date:  2015-09-09       Impact factor: 4.460

Review 5.  Peripheral blood smear image analysis: A comprehensive review.

Authors:  Emad A Mohammed; Mostafa M A Mohamed; Behrouz H Far; Christopher Naugler
Journal:  J Pathol Inform       Date:  2014-03-28

6.  An Intelligent Decision Support System for Leukaemia Diagnosis using Microscopic Blood Images.

Authors:  Siew Chin Neoh; Worawut Srisukkham; Li Zhang; Stephen Todryk; Brigit Greystoke; Chee Peng Lim; Mohammed Alamgir Hossain; Nauman Aslam
Journal:  Sci Rep       Date:  2015-10-09       Impact factor: 4.379

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.